Transient Linear Flow Analysis of Multi-Fractured Horizontal Wells Considering Three-Phase Flow and Pressure-Dependent Rock Properties

2018 ◽  
Author(s):  
H. Behmanesh ◽  
H. Hamdi ◽  
C. R. Clarkson ◽  
J. M. Thompson ◽  
D. M. Anderson ◽  
...  
Keyword(s):  
Flow Analysis ◽  
Horizontal Wells ◽  
Rock Properties ◽  
Phase Flow ◽  
Linear Flow ◽  
Three Phase ◽  
Three Phase Flow ◽  
Fractured Horizontal Wells

Stratified three phase flow in pipes

1996 ◽  
Vol 22 ◽  
pp. 118
Author(s):  
Y Taitel
Keyword(s):  
Phase Flow ◽  
Three Phase ◽  
Three Phase Flow

Numerical Simulation of the Three Phase Flow Formed During the Containment of an Oil-Methane Leak Using the DIFIS System

2015 ◽  
Vol 9 (6) ◽  
pp. 576
Author(s):  
Dimitrios Periklis Giannoulis ◽  
Dionissios P. Margaris
Keyword(s):  
Numerical Simulation ◽  
Phase Flow ◽  
Three Phase ◽  
Three Phase Flow

On the Relationship Between Capillary Pressure, Saturation, and Interfacial Area for Three-Phase Flow in Water-Wet Porous Media

2021 ◽  
pp. 103905
Author(s):  
Rebecca Paustian ◽  
Linnéa Andersson ◽  
Johan Olav Helland ◽  
Dorthe Wildenschild
Keyword(s):  
Porous Media ◽  
Capillary Pressure ◽  
Interfacial Area ◽  
Phase Flow ◽  
Three Phase ◽  
Three Phase Flow ◽  
The Relationship

scholarly journals Correction to Flow Rate Profile Interpretation for a Two-Phase Flow in Multistage Fractured Horizontal Wells by Inversion of DTS Data

ACS Omega ◽  
2020 ◽  
Vol 5 (41) ◽  
pp. 26955-26955
Author(s):  
Hongwen Luo ◽  
Beibei Jiang ◽  
Haitao Li ◽  
Ying Li ◽  
Zhangxin Chen
Keyword(s):  
Flow Rate ◽  
Two Phase Flow ◽  
Horizontal Wells ◽  
Phase Flow ◽  
Two Phase ◽  
Fractured Horizontal Wells ◽  
Rate Profile

Hybrid Mathematical Modelling of Three-Phase Flow in Porous Media: Application to Water-Alternating-Gas Injection

2021 ◽  
pp. 103966
Author(s):  
Shokufe Afzali ◽  
Sohrab Zendehboudi ◽  
Omid Mohammadzadeh ◽  
Nima Rezaei
Keyword(s):  
Porous Media ◽  
Mathematical Modelling ◽  
Gas Injection ◽  
Flow In Porous Media ◽  
Phase Flow ◽  
Water Alternating Gas ◽  
Three Phase ◽  
Three Phase Flow

scholarly journals Application of Artificial Intelligence and Gamma Attenuation Techniques for Predicting Gas–Oil–Water Volume Fraction in Annular Regime of Three-Phase Flow Independent of Oil Pipeline’s Scale Layer

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1460
Author(s):  
Abdulaziz S. Alkabaa ◽  
Ehsan Nazemi ◽  
Osman Taylan ◽  
El Mostafa Kalmoun
Keyword(s):  
Gamma Radiation ◽  
Volume Fraction ◽  
Phase Flow ◽  
Gas Oil ◽  
Oil Pipeline ◽  
Intelligent Technique ◽  
Scale Layer ◽  
Three Phase ◽  
Three Phase Flow ◽  
Annular Regime

To the best knowledge of the authors, in former studies in the field of measuring volume fraction of gas, oil, and water components in a three-phase flow using gamma radiation technique, the existence of a scale layer has not been considered. The formed scale layer usually has a higher density in comparison to the fluid flow inside the oil pipeline, which can lead to high photon attenuation and, consequently, reduce the measuring precision of three-phase flow meter. The purpose of this study is to present an intelligent gamma radiation-based, nondestructive technique with the ability to measure volume fraction of gas, oil, and water components in the annular regime of a three-phase flow independent of the scale layer. Since, in this problem, there are several unknown parameters, such as gas, oil, and water components with different amounts and densities and scale layers with different thicknesses, it is not possible to measure the volume fraction using a conventional gamma radiation system. In this study, a system including a 241Am-133Ba dual energy source and two transmission detectors was used. The first detector was located diametrically in front of the source. For the second detector, at first, a sensitivity investigation was conducted in order to find the optimum position. The four extracted signals in both detectors (counts under photo peaks of both detectors) were used as inputs of neural network, and volume fractions of gas and oil components were utilized as the outputs. Using the proposed intelligent technique, volume fraction of each component was predicted independent of the barium sulfate scale layer, with a maximum MAE error of 3.66%.

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